Clinical instruments currently in use for analyzing the components of a blood sample employ a wide variety of electrically and optically based techniques to discriminate and quantify platelets from other cells or particles, such as red blood cells, including normal red blood cells and microcytic red blood cells, red blood cell fragments, oversized platelets and platelet aggregates.
A measurement utilizing monoclonal antibodies which bind specifically to platelet cells is widely recognized as the most accurate method, even in the presence of interfering substances, such as platelet clumps, giant or oversized platelets, microcytic red blood cells and red blood cell fragments. Preparation of the sample for this method requires multiple dilutions and incubation periods that can range to well over ten minutes. To collect emitted optical signals created by this method, in addition to forward light scatter measurements, this method requires the optical means to collect the fluorescent light and highly sensitive sensors, such as PMTs, to accurately measure the fluorescent signal. The expense associated with this hardware is prohibitive with low cost instrumentation. In addition, long incubation periods are not favorable for instruments with high sample throughput requirements. An additional drawback to monoclonal antibodies is the relative expense of the reagent.
A second method that has been recognized to provide accurate platelet enumeration is that of treating the blood specimen with a fluorescent dye and identifying the platelet cell by a fluorescence measurement. Although this method typically does not require extended incubation periods and the dye reagent is relatively inexpensive compared to monoclonal antibodies, there is an additional expense associated with the hardware to perform this measurement. Moreover, some dyes are associated with non specific binding to various cell types.
Other methods exist which identify platelet cells by means of a strictly optical measurement. Various disadvantages are associated with these methods. First, all of these methods require multiple sensors, adding complexity and expense to their respective instruments. Additionally, these methods have limitations discriminating red blood cells from platelet cells in the presence of interfering substances.
There are several methods known to those skilled in the art for utilizing light scatter for identification of white blood cells. Moreover, U.S. Pat. No. 5,616,501 teaches a method of determining reticulocytes in a blood sample by using a ghosting reagent and preferably an RNA precipitating dye with light scatter measurements.
Hansen U.S. Pat. No. 4,577,964, discloses a method which utilizes low angle light scatter measurement and pulse duration to discriminate platelet cells from red blood cells in a diluted blood specimen. Inherent in this method is the fact that, although the blood sample is diluted, red blood cells and platelet cells maintain their respective volumes and the measurement is based upon their optical characteristics. In other words, cells in the diluted sample maintain their native states. This method provides the advantage of a single optical sensor for the light scatter measurement and an electronic measurement derived from the light scatter signal for the pulse duration. Although providing relatively accurate and precise platelet enumeration for normal samples without interfering substances, limitations exist for discriminating red blood cells from platelets in the presence of interfering substances such as platelet clumps.
Recent advances in technology have demonstrated improvements in the measurement of pulse width, or time-of-flight measurements. This method collects a broad angle forward light scatter signal and calculates a time-of-flight value for each blood cell event from a diluted blood specimen. The buffer solution maintains the red blood cells and the platelet cells in their native states. As shown in the scatterplot of FIG. 1, this method yields an accurate and precise platelet enumeration, region 11, for normal samples without interfering substances. Region 12 corresponds to the RBC population and region 13 corresponds to the RBC coincidence. However, this method is still subject to limitations in the presence of interfering substances such as in FIG. 3 region 31 (giant platelets or oversize platelets), FIG. 5 region 51 (platelet clumps or aggregates), and FIG. 7 region 71 (RBC fragments).
For example, in some cases, the volume of platelet clumps and oversized platelets tends to approach that of a normal red blood cell population. Consequently, their light scatter signal often overlaps a portion of the red blood cell population thereby preventing proper identification of the platelet cells, as shown at region 21 in the scatterplot of FIG. 2, and region 41 in the scatterplot of FIG. 4. (The scatterplot of FIG. 3 corresponds to that of FIG. 2 with the red blood cells removed from region 31, while the scatterplot of FIG. 5 corresponds to that of FIG. 4, with the red blood cells removed from region 51.) This condition often results in the platelet population being under counted.
Conversely, the volume of microcytic red blood cells and red blood cell fragments can approach that of normal platelet cells thereby causing their scatter signal to overlap that of platelet cells, as shown at region 61 in the scatterplot of FIG. 6. (FIG. 7 corresponds to the scatterplot of FIG. 6, with the platelets removed from region 71.) Not being distinguished from the platelets, these red blood cells are counted as platelets causing the platelet population to be over counted.
In addition to potential interferences from abnormal red blood cell and platelet populations, normal white blood cells may also tend to exhibit the same or similar light scatter and pulse duration measurement results as those of red blood cells. In normal samples, the ratio of red blood cell to white blood cells is typically about a thousand to one. Consequently, overlap between red blood cells and white blood cells imparts minimal impact to the red blood cell or platelet counts. However, certain medical conditions, such as severe infection or leukemia, cause elevated levels of white blood cells. Furthermore, conditions such as anemia or excessive bleeding cause a substantial decrease in the levels of red blood cells. Either of these types of conditions, or a combination of these types of conditions results in an inaccurate estimation of the red blood cell count, which in turn results in an inaccurate estimation of the platelet count.